Triple
T26896994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arendelle Castle |
E677921
|
entity |
| Predicate | inspiredByRealLocation |
P113256
|
FINISHED |
| Object | Akershus Fortress, Oslo |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Akershus Fortress, Oslo | Statement: [Arendelle Castle, inspiredByRealLocation, Akershus Fortress, Oslo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inspiredByRealLocation Context triple: [Arendelle Castle, inspiredByRealLocation, Akershus Fortress, Oslo]
-
A.
inspiredByPlace
Indicates that something (such as a work, idea, or creation) originates from or is significantly influenced by a particular location or environment.
-
B.
portrayedByRealWorldLocation
chosen
Indicates that a fictional or represented location is depicted or substituted by an actual real-world location.
-
C.
inspiredByRealStreet
Indicates that something is based on, modeled after, or creatively derived from an actual, existing street in the real world.
-
D.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
-
E.
fictionalLocationAssociatedWith
Indicates a relationship where a fictional entity (such as a character, event, or work) is connected to or set in a particular fictional location.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 5:48 a.m.